Overview

Dataset statistics

Number of variables16
Number of observations48906
Missing cells20141
Missing cells (%)2.6%
Duplicate rows11
Duplicate rows (%)< 0.1%
Total size in memory23.5 MiB
Average record size in memory504.1 B

Variable types

Numeric10
Text3
Categorical2
DateTime1

Alerts

Dataset has 11 (< 0.1%) duplicate rowsDuplicates
host_id is highly overall correlated with idHigh correlation
id is highly overall correlated with host_idHigh correlation
latitude is highly overall correlated with neighbourhood_groupHigh correlation
longitude is highly overall correlated with neighbourhood_groupHigh correlation
neighbourhood_group is highly overall correlated with latitude and 1 other fieldsHigh correlation
number_of_reviews is highly overall correlated with reviews_per_monthHigh correlation
reviews_per_month is highly overall correlated with number_of_reviewsHigh correlation
last_review has 10052 (20.6%) missing valuesMissing
reviews_per_month has 10052 (20.6%) missing valuesMissing
minimum_nights is highly skewed (γ1 = 21.81741566)Skewed
number_of_reviews has 10052 (20.6%) zerosZeros
availability_365 has 17536 (35.9%) zerosZeros

Reproduction

Analysis started2026-02-09 15:31:05.798000
Analysis finished2026-02-09 15:31:24.483854
Duration18.69 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

id
Real number (ℝ)

High correlation 

Distinct48895
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19012867
Minimum2539
Maximum36487245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size382.2 KiB
2026-02-09T21:01:24.639851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2539
5-th percentile1214273.8
Q19464662.5
median19675452
Q329150848
95-th percentile35258667
Maximum36487245
Range36484706
Interquartile range (IQR)19686186

Descriptive statistics

Standard deviation10985573
Coefficient of variation (CV)0.57779676
Kurtosis-1.2278603
Mean19012867
Median Absolute Deviation (MAD)9908588.5
Skewness-0.090174411
Sum9.2984328 × 1011
Variance1.2068282 × 1014
MonotonicityNot monotonic
2026-02-09T21:01:24.806851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54412
 
< 0.1%
50992
 
< 0.1%
51212
 
< 0.1%
51782
 
< 0.1%
52032
 
< 0.1%
52382
 
< 0.1%
52952
 
< 0.1%
58032
 
< 0.1%
60212
 
< 0.1%
60902
 
< 0.1%
Other values (48885)48886
> 99.9%
ValueCountFrequency (%)
25391
< 0.1%
25951
< 0.1%
36471
< 0.1%
38311
< 0.1%
50221
< 0.1%
50992
< 0.1%
51212
< 0.1%
51782
< 0.1%
52032
< 0.1%
52382
< 0.1%
ValueCountFrequency (%)
364872451
< 0.1%
364856091
< 0.1%
364854311
< 0.1%
364850571
< 0.1%
364846651
< 0.1%
364843631
< 0.1%
364840871
< 0.1%
364831521
< 0.1%
364830101
< 0.1%
364828091
< 0.1%

name
Text

Distinct47896
Distinct (%)98.0%
Missing16
Missing (%)< 0.1%
Memory size4.5 MiB
2026-02-09T21:01:25.221766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length179
Median length78
Mean length36.902557
Min length1

Characters and Unicode

Total characters1804166
Distinct characters776
Distinct categories20 ?
Distinct scripts11 ?
Distinct blocks17 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47239 ?
Unique (%)96.6%

Sample

1st rowClean & quiet apt home by the park
2nd rowSkylit Midtown Castle
3rd rowTHE VILLAGE OF HARLEM....NEW YORK !
4th rowCozy Entire Floor of Brownstone
5th rowEntire Apt: Spacious Studio/Loft by central park
ValueCountFrequency (%)
in16746
 
5.6%
room10031
 
3.4%
8416
 
2.8%
bedroom7602
 
2.5%
private7151
 
2.4%
apartment6695
 
2.2%
cozy4987
 
1.7%
apt4619
 
1.5%
brooklyn4049
 
1.4%
studio3989
 
1.3%
Other values (12552)224312
75.1%
2026-02-09T21:01:25.773855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
251389
 
13.9%
e124631
 
6.9%
o122315
 
6.8%
t105265
 
5.8%
a103583
 
5.7%
r97943
 
5.4%
i94645
 
5.2%
n94617
 
5.2%
l51733
 
2.9%
m49119
 
2.7%
Other values (766)708926
39.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1206204
66.9%
Uppercase Letter270587
 
15.0%
Space Separator251393
 
13.9%
Other Punctuation33852
 
1.9%
Decimal Number25326
 
1.4%
Dash Punctuation6861
 
0.4%
Math Symbol2736
 
0.2%
Other Letter2547
 
0.1%
Close Punctuation1537
 
0.1%
Open Punctuation1395
 
0.1%
Other values (10)1728
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
82
 
3.2%
46
 
1.8%
44
 
1.7%
41
 
1.6%
38
 
1.5%
37
 
1.5%
36
 
1.4%
36
 
1.4%
30
 
1.2%
29
 
1.1%
Other values (520)2128
83.5%
Lowercase Letter
ValueCountFrequency (%)
e124631
 
10.3%
o122315
 
10.1%
t105265
 
8.7%
a103583
 
8.6%
r97943
 
8.1%
i94645
 
7.8%
n94617
 
7.8%
l51733
 
4.3%
m49119
 
4.1%
s48107
 
4.0%
Other values (58)314246
26.1%
Other Symbol
ValueCountFrequency (%)
266
30.3%
168
19.1%
105
 
11.9%
38
 
4.3%
35
 
4.0%
34
 
3.9%
25
 
2.8%
15
 
1.7%
15
 
1.7%
14
 
1.6%
Other values (50)164
18.7%
Uppercase Letter
ValueCountFrequency (%)
B29970
 
11.1%
S26473
 
9.8%
C20987
 
7.8%
A19431
 
7.2%
R17939
 
6.6%
P14616
 
5.4%
E14361
 
5.3%
L14060
 
5.2%
M11939
 
4.4%
N11710
 
4.3%
Other values (33)89101
32.9%
Other Punctuation
ValueCountFrequency (%)
,9180
27.1%
!7856
23.2%
/5230
15.4%
.4375
12.9%
&3183
 
9.4%
'1075
 
3.2%
*1021
 
3.0%
:597
 
1.8%
#565
 
1.7%
"294
 
0.9%
Other values (11)476
 
1.4%
Math Symbol
ValueCountFrequency (%)
+1380
50.4%
|992
36.3%
~271
 
9.9%
=34
 
1.2%
>25
 
0.9%
<20
 
0.7%
6
 
0.2%
4
 
0.1%
2
 
0.1%
1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
18665
34.2%
26831
27.0%
32560
 
10.1%
52164
 
8.5%
02115
 
8.4%
41307
 
5.2%
6569
 
2.2%
7450
 
1.8%
8399
 
1.6%
9266
 
1.1%
Close Punctuation
ValueCountFrequency (%)
)1480
96.3%
]37
 
2.4%
}9
 
0.6%
8
 
0.5%
3
 
0.2%
Open Punctuation
ValueCountFrequency (%)
(1339
96.0%
[36
 
2.6%
{9
 
0.6%
8
 
0.6%
3
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
-6787
98.9%
47
 
0.7%
26
 
0.4%
1
 
< 0.1%
Modifier Letter
ValueCountFrequency (%)
21
56.8%
11
29.7%
5
 
13.5%
Modifier Symbol
ValueCountFrequency (%)
^9
56.2%
`4
25.0%
´3
 
18.8%
Space Separator
ValueCountFrequency (%)
251389
> 99.9%
 4
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
200
84.0%
38
 
16.0%
Nonspacing Mark
ValueCountFrequency (%)
165
92.2%
14
 
7.8%
Connector Punctuation
ValueCountFrequency (%)
_42
97.7%
1
 
2.3%
Initial Punctuation
ValueCountFrequency (%)
40
83.3%
8
 
16.7%
Control
ValueCountFrequency (%)
185
100.0%
Currency Symbol
ValueCountFrequency (%)
$94
100.0%
Other Number
ValueCountFrequency (%)
²9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1476588
81.8%
Common324649
 
18.0%
Han2237
 
0.1%
Cyrillic191
 
< 0.1%
Inherited179
 
< 0.1%
Katakana136
 
< 0.1%
Hiragana70
 
< 0.1%
Hangul70
 
< 0.1%
Hebrew31
 
< 0.1%
Georgian13
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
82
 
3.7%
46
 
2.1%
44
 
2.0%
41
 
1.8%
38
 
1.7%
37
 
1.7%
36
 
1.6%
36
 
1.6%
30
 
1.3%
29
 
1.3%
Other values (401)1818
81.3%
Common
ValueCountFrequency (%)
251389
77.4%
,9180
 
2.8%
18665
 
2.7%
!7856
 
2.4%
26831
 
2.1%
-6787
 
2.1%
/5230
 
1.6%
.4375
 
1.3%
&3183
 
1.0%
32560
 
0.8%
Other values (123)18593
 
5.7%
Latin
ValueCountFrequency (%)
e124631
 
8.4%
o122315
 
8.3%
t105265
 
7.1%
a103583
 
7.0%
r97943
 
6.6%
i94645
 
6.4%
n94617
 
6.4%
l51733
 
3.5%
m49119
 
3.3%
s48107
 
3.3%
Other values (68)584630
39.6%
Hangul
ValueCountFrequency (%)
7
 
10.0%
3
 
4.3%
3
 
4.3%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (38)43
61.4%
Cyrillic
ValueCountFrequency (%)
а26
13.6%
о18
 
9.4%
т17
 
8.9%
н15
 
7.9%
е13
 
6.8%
к11
 
5.8%
р11
 
5.8%
м10
 
5.2%
в9
 
4.7%
с9
 
4.7%
Other values (23)52
27.2%
Katakana
ValueCountFrequency (%)
14
 
10.3%
12
 
8.8%
10
 
7.4%
9
 
6.6%
9
 
6.6%
9
 
6.6%
8
 
5.9%
7
 
5.1%
6
 
4.4%
6
 
4.4%
Other values (22)46
33.8%
Hiragana
ValueCountFrequency (%)
16
22.9%
7
10.0%
7
10.0%
6
 
8.6%
5
 
7.1%
4
 
5.7%
4
 
5.7%
3
 
4.3%
2
 
2.9%
2
 
2.9%
Other values (13)14
20.0%
Hebrew
ValueCountFrequency (%)
ו5
16.1%
י5
16.1%
ר4
12.9%
ב4
12.9%
ע2
 
6.5%
ת2
 
6.5%
ה2
 
6.5%
ס1
 
3.2%
ג1
 
3.2%
מ1
 
3.2%
Other values (4)4
12.9%
Inherited
ValueCountFrequency (%)
165
92.2%
14
 
7.8%
Georgian
ValueCountFrequency (%)
13
100.0%
Devanagari
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1799673
99.8%
CJK2237
 
0.1%
Misc Symbols500
 
< 0.1%
None431
 
< 0.1%
Punctuation423
 
< 0.1%
Dingbats320
 
< 0.1%
Cyrillic191
 
< 0.1%
VS179
 
< 0.1%
Hiragana70
 
< 0.1%
Hangul70
 
< 0.1%
Other values (7)72
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
251389
 
14.0%
e124631
 
6.9%
o122315
 
6.8%
t105265
 
5.8%
a103583
 
5.8%
r97943
 
5.4%
i94645
 
5.3%
n94617
 
5.3%
l51733
 
2.9%
m49119
 
2.7%
Other values (86)704433
39.1%
Misc Symbols
ValueCountFrequency (%)
266
53.2%
105
 
21.0%
38
 
7.6%
15
 
3.0%
11
 
2.2%
8
 
1.6%
6
 
1.2%
6
 
1.2%
6
 
1.2%
6
 
1.2%
Other values (12)33
 
6.6%
Punctuation
ValueCountFrequency (%)
200
47.3%
62
 
14.7%
47
 
11.1%
40
 
9.5%
38
 
9.0%
26
 
6.1%
8
 
1.9%
1
 
0.2%
1
 
0.2%
Dingbats
ValueCountFrequency (%)
168
52.5%
34
 
10.6%
25
 
7.8%
15
 
4.7%
14
 
4.4%
11
 
3.4%
8
 
2.5%
6
 
1.9%
5
 
1.6%
4
 
1.2%
Other values (13)30
 
9.4%
VS
ValueCountFrequency (%)
165
92.2%
14
 
7.8%
CJK
ValueCountFrequency (%)
82
 
3.7%
46
 
2.1%
44
 
2.0%
41
 
1.8%
38
 
1.7%
37
 
1.7%
36
 
1.6%
36
 
1.6%
30
 
1.3%
29
 
1.3%
Other values (401)1818
81.3%
None
ValueCountFrequency (%)
35
 
8.1%
à28
 
6.5%
ó24
 
5.6%
21
 
4.9%
é16
 
3.7%
15
 
3.5%
14
 
3.2%
·13
 
3.0%
12
 
2.8%
11
 
2.6%
Other values (70)242
56.1%
Cyrillic
ValueCountFrequency (%)
а26
13.6%
о18
 
9.4%
т17
 
8.9%
н15
 
7.9%
е13
 
6.8%
к11
 
5.8%
р11
 
5.8%
м10
 
5.2%
в9
 
4.7%
с9
 
4.7%
Other values (23)52
27.2%
Hiragana
ValueCountFrequency (%)
16
22.9%
7
10.0%
7
10.0%
6
 
8.6%
5
 
7.1%
4
 
5.7%
4
 
5.7%
3
 
4.3%
2
 
2.9%
2
 
2.9%
Other values (13)14
20.0%
Georgian
ValueCountFrequency (%)
13
100.0%
Hangul
ValueCountFrequency (%)
7
 
10.0%
3
 
4.3%
3
 
4.3%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (38)43
61.4%
Hebrew
ValueCountFrequency (%)
ו5
16.1%
י5
16.1%
ר4
12.9%
ב4
12.9%
ע2
 
6.5%
ת2
 
6.5%
ה2
 
6.5%
ס1
 
3.2%
ג1
 
3.2%
מ1
 
3.2%
Other values (4)4
12.9%
Math Operators
ValueCountFrequency (%)
4
57.1%
2
28.6%
1
 
14.3%
Misc Technical
ValueCountFrequency (%)
4
57.1%
1
 
14.3%
1
 
14.3%
1
 
14.3%
Geometric Shapes
ValueCountFrequency (%)
4
36.4%
2
18.2%
2
18.2%
2
18.2%
1
 
9.1%
Devanagari
ValueCountFrequency (%)
2
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%

host_id
Real number (ℝ)

High correlation 

Distinct37457
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67604804
Minimum2438
Maximum2.7432131 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size382.2 KiB
2026-02-09T21:01:25.904851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2438
5-th percentile810104
Q17809567.2
median30784628
Q31.0743442 × 108
95-th percentile2.4175623 × 108
Maximum2.7432131 × 108
Range2.7431888 × 108
Interquartile range (IQR)99624856

Descriptive statistics

Standard deviation78608664
Coefficient of variation (CV)1.1627674
Kurtosis0.16982068
Mean67604804
Median Absolute Deviation (MAD)27536856
Skewness1.2064858
Sum3.3062805 × 1012
Variance6.1793221 × 1015
MonotonicityNot monotonic
2026-02-09T21:01:26.054848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
219517861327
 
0.7%
107434423232
 
0.5%
30283594121
 
0.2%
137358866103
 
0.2%
1224305196
 
0.2%
1609895896
 
0.2%
6139196391
 
0.2%
2254157387
 
0.2%
20038061065
 
0.1%
750364352
 
0.1%
Other values (37447)47636
97.4%
ValueCountFrequency (%)
24381
 
< 0.1%
25711
 
< 0.1%
27876
< 0.1%
28452
 
< 0.1%
28681
 
< 0.1%
28812
 
< 0.1%
31511
 
< 0.1%
32111
 
< 0.1%
34151
 
< 0.1%
35631
 
< 0.1%
ValueCountFrequency (%)
2743213131
< 0.1%
2743114611
< 0.1%
2743076001
< 0.1%
2742984531
< 0.1%
2742732841
< 0.1%
2742256171
< 0.1%
2741954581
< 0.1%
2741883861
< 0.1%
2741033831
< 0.1%
2740799641
< 0.1%
Distinct11452
Distinct (%)23.4%
Missing21
Missing (%)< 0.1%
Memory size3.0 MiB
2026-02-09T21:01:26.367850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length35
Median length31
Mean length6.124619
Min length1

Characters and Unicode

Total characters299402
Distinct characters206
Distinct categories15 ?
Distinct scripts7 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6900 ?
Unique (%)14.1%

Sample

1st rowJohn
2nd rowJennifer
3rd rowElisabeth
4th rowLisaRoxanne
5th rowLaura
ValueCountFrequency (%)
1121
 
2.1%
and625
 
1.1%
michael460
 
0.8%
david449
 
0.8%
sonder423
 
0.8%
nyc338
 
0.6%
john337
 
0.6%
alex330
 
0.6%
laura293
 
0.5%
maria244
 
0.4%
Other values (10259)49980
91.5%
2026-02-09T21:01:26.831855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a37937
 
12.7%
e28682
 
9.6%
i24291
 
8.1%
n24098
 
8.0%
r17864
 
6.0%
l15333
 
5.1%
o12743
 
4.3%
t9401
 
3.1%
s9147
 
3.1%
h9042
 
3.0%
Other values (196)110864
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter235955
78.8%
Uppercase Letter54836
 
18.3%
Space Separator5813
 
1.9%
Other Punctuation1595
 
0.5%
Open Punctuation381
 
0.1%
Close Punctuation379
 
0.1%
Dash Punctuation208
 
0.1%
Other Letter110
 
< 0.1%
Decimal Number83
 
< 0.1%
Math Symbol34
 
< 0.1%
Other values (5)8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
5.5%
5
 
4.5%
5
 
4.5%
5
 
4.5%
4
 
3.6%
3
 
2.7%
3
 
2.7%
3
 
2.7%
2
 
1.8%
2
 
1.8%
Other values (62)72
65.5%
Lowercase Letter
ValueCountFrequency (%)
a37937
16.1%
e28682
12.2%
i24291
10.3%
n24098
10.2%
r17864
 
7.6%
l15333
 
6.5%
o12743
 
5.4%
t9401
 
4.0%
s9147
 
3.9%
h9042
 
3.8%
Other values (54)47417
20.1%
Uppercase Letter
ValueCountFrequency (%)
A6461
11.8%
J5458
 
10.0%
M5300
 
9.7%
S4745
 
8.7%
C3738
 
6.8%
L2886
 
5.3%
D2752
 
5.0%
K2619
 
4.8%
R2566
 
4.7%
E2363
 
4.3%
Other values (28)15948
29.1%
Other Punctuation
ValueCountFrequency (%)
&1163
72.9%
.309
 
19.4%
/41
 
2.6%
,35
 
2.2%
'25
 
1.6%
@8
 
0.5%
"6
 
0.4%
!4
 
0.3%
:2
 
0.1%
?1
 
0.1%
Decimal Number
ValueCountFrequency (%)
520
24.1%
714
16.9%
013
15.7%
211
13.3%
47
 
8.4%
17
 
8.4%
64
 
4.8%
34
 
4.8%
82
 
2.4%
91
 
1.2%
Space Separator
ValueCountFrequency (%)
5807
99.9%
6
 
0.1%
Open Punctuation
ValueCountFrequency (%)
(381
100.0%
Close Punctuation
ValueCountFrequency (%)
)379
100.0%
Dash Punctuation
ValueCountFrequency (%)
-208
100.0%
Math Symbol
ValueCountFrequency (%)
+34
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Format
ValueCountFrequency (%)
2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%
Currency Symbol
ValueCountFrequency (%)
£1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin290735
97.1%
Common8501
 
2.8%
Han91
 
< 0.1%
Cyrillic56
 
< 0.1%
Hangul11
 
< 0.1%
Hebrew5
 
< 0.1%
Hiragana3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a37937
 
13.0%
e28682
 
9.9%
i24291
 
8.4%
n24098
 
8.3%
r17864
 
6.1%
l15333
 
5.3%
o12743
 
4.4%
t9401
 
3.2%
s9147
 
3.1%
h9042
 
3.1%
Other values (70)102197
35.2%
Han
ValueCountFrequency (%)
6
 
6.6%
5
 
5.5%
5
 
5.5%
5
 
5.5%
4
 
4.4%
3
 
3.3%
3
 
3.3%
3
 
3.3%
2
 
2.2%
2
 
2.2%
Other values (45)53
58.2%
Common
ValueCountFrequency (%)
5807
68.3%
&1163
 
13.7%
(381
 
4.5%
)379
 
4.5%
.309
 
3.6%
-208
 
2.4%
/41
 
0.5%
,35
 
0.4%
+34
 
0.4%
'25
 
0.3%
Other values (22)119
 
1.4%
Cyrillic
ValueCountFrequency (%)
н6
10.7%
а6
10.7%
е6
10.7%
А4
 
7.1%
и4
 
7.1%
л4
 
7.1%
с3
 
5.4%
к3
 
5.4%
р3
 
5.4%
й3
 
5.4%
Other values (12)14
25.0%
Hangul
ValueCountFrequency (%)
2
18.2%
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Hebrew
ValueCountFrequency (%)
ל1
20.0%
א1
20.0%
י1
20.0%
נ1
20.0%
ד1
20.0%
Hiragana
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII298977
99.9%
None247
 
0.1%
CJK91
 
< 0.1%
Cyrillic56
 
< 0.1%
Hangul11
 
< 0.1%
Punctuation10
 
< 0.1%
Hebrew5
 
< 0.1%
Hiragana3
 
< 0.1%
Misc Symbols2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a37937
 
12.7%
e28682
 
9.6%
i24291
 
8.1%
n24098
 
8.1%
r17864
 
6.0%
l15333
 
5.1%
o12743
 
4.3%
t9401
 
3.1%
s9147
 
3.1%
h9042
 
3.0%
Other values (69)110439
36.9%
None
ValueCountFrequency (%)
é107
43.3%
í24
 
9.7%
á22
 
8.9%
ú19
 
7.7%
ë13
 
5.3%
ô11
 
4.5%
ó9
 
3.6%
è7
 
2.8%
ç5
 
2.0%
ï4
 
1.6%
Other values (19)26
 
10.5%
Cyrillic
ValueCountFrequency (%)
н6
10.7%
а6
10.7%
е6
10.7%
А4
 
7.1%
и4
 
7.1%
л4
 
7.1%
с3
 
5.4%
к3
 
5.4%
р3
 
5.4%
й3
 
5.4%
Other values (12)14
25.0%
CJK
ValueCountFrequency (%)
6
 
6.6%
5
 
5.5%
5
 
5.5%
5
 
5.5%
4
 
4.4%
3
 
3.3%
3
 
3.3%
3
 
3.3%
2
 
2.2%
2
 
2.2%
Other values (45)53
58.2%
Punctuation
ValueCountFrequency (%)
6
60.0%
2
 
20.0%
2
 
20.0%
Misc Symbols
ValueCountFrequency (%)
2
100.0%
Hangul
ValueCountFrequency (%)
2
18.2%
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Hiragana
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Hebrew
ValueCountFrequency (%)
ל1
20.0%
א1
20.0%
י1
20.0%
נ1
20.0%
ד1
20.0%

neighbourhood_group
Categorical

High correlation 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.0 MiB
Manhattan
21669 
Brooklyn
20107 
Queens
5666 
Bronx
 
1091
Staten Island
 
373

Length

Max length13
Median length9
Mean length8.1825747
Min length5

Characters and Unicode

Total characters400177
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBrooklyn
2nd rowManhattan
3rd rowManhattan
4th rowBrooklyn
5th rowManhattan

Common Values

ValueCountFrequency (%)
Manhattan21669
44.3%
Brooklyn20107
41.1%
Queens5666
 
11.6%
Bronx1091
 
2.2%
Staten Island373
 
0.8%

Length

2026-02-09T21:01:26.952857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-02-09T21:01:27.066858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
manhattan21669
44.0%
brooklyn20107
40.8%
queens5666
 
11.5%
bronx1091
 
2.2%
staten373
 
0.8%
island373
 
0.8%

Most occurring characters

ValueCountFrequency (%)
n70948
17.7%
a65753
16.4%
t44084
11.0%
o41305
10.3%
M21669
 
5.4%
h21669
 
5.4%
B21198
 
5.3%
r21198
 
5.3%
l20480
 
5.1%
y20107
 
5.0%
Other values (10)51766
12.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter350525
87.6%
Uppercase Letter49279
 
12.3%
Space Separator373
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n70948
20.2%
a65753
18.8%
t44084
12.6%
o41305
11.8%
h21669
 
6.2%
r21198
 
6.0%
l20480
 
5.8%
y20107
 
5.7%
k20107
 
5.7%
e11705
 
3.3%
Other values (4)13169
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
M21669
44.0%
B21198
43.0%
Q5666
 
11.5%
S373
 
0.8%
I373
 
0.8%
Space Separator
ValueCountFrequency (%)
373
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin399804
99.9%
Common373
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n70948
17.7%
a65753
16.4%
t44084
11.0%
o41305
10.3%
M21669
 
5.4%
h21669
 
5.4%
B21198
 
5.3%
r21198
 
5.3%
l20480
 
5.1%
y20107
 
5.0%
Other values (9)51393
12.9%
Common
ValueCountFrequency (%)
373
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII400177
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n70948
17.7%
a65753
16.4%
t44084
11.0%
o41305
10.3%
M21669
 
5.4%
h21669
 
5.4%
B21198
 
5.3%
r21198
 
5.3%
l20480
 
5.1%
y20107
 
5.0%
Other values (10)51766
12.9%
Distinct221
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 MiB
2026-02-09T21:01:27.350853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length26
Median length17
Mean length11.895105
Min length4

Characters and Unicode

Total characters581742
Distinct characters54
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowKensington
2nd rowMidtown
3rd rowHarlem
4th rowClinton Hill
5th rowEast Harlem
ValueCountFrequency (%)
east6592
 
8.3%
side4683
 
5.9%
williamsburg3921
 
5.0%
harlem3775
 
4.8%
upper3772
 
4.8%
bedford-stuyvesant3715
 
4.7%
heights3586
 
4.5%
village3165
 
4.0%
west2763
 
3.5%
bushwick2465
 
3.1%
Other values (233)40690
51.4%
2026-02-09T21:01:27.749713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e53488
 
9.2%
i42292
 
7.3%
s39633
 
6.8%
t38597
 
6.6%
a37613
 
6.5%
l34459
 
5.9%
r33674
 
5.8%
30221
 
5.2%
n26104
 
4.5%
o24036
 
4.1%
Other values (44)221625
38.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter461216
79.3%
Uppercase Letter83957
 
14.4%
Space Separator30221
 
5.2%
Dash Punctuation4252
 
0.7%
Other Punctuation2096
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e53488
11.6%
i42292
 
9.2%
s39633
 
8.6%
t38597
 
8.4%
a37613
 
8.2%
l34459
 
7.5%
r33674
 
7.3%
n26104
 
5.7%
o24036
 
5.2%
d19668
 
4.3%
Other values (15)111652
24.2%
Uppercase Letter
ValueCountFrequency (%)
H11904
14.2%
S11489
13.7%
B8375
10.0%
W8190
9.8%
E7084
8.4%
C5328
 
6.3%
U3836
 
4.6%
G3723
 
4.4%
F3281
 
3.9%
V3210
 
3.8%
Other values (14)17537
20.9%
Other Punctuation
ValueCountFrequency (%)
'1970
94.0%
.124
 
5.9%
,2
 
0.1%
Space Separator
ValueCountFrequency (%)
30221
100.0%
Dash Punctuation
ValueCountFrequency (%)
-4252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin545173
93.7%
Common36569
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e53488
 
9.8%
i42292
 
7.8%
s39633
 
7.3%
t38597
 
7.1%
a37613
 
6.9%
l34459
 
6.3%
r33674
 
6.2%
n26104
 
4.8%
o24036
 
4.4%
d19668
 
3.6%
Other values (39)195609
35.9%
Common
ValueCountFrequency (%)
30221
82.6%
-4252
 
11.6%
'1970
 
5.4%
.124
 
0.3%
,2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII581742
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e53488
 
9.2%
i42292
 
7.3%
s39633
 
6.8%
t38597
 
6.6%
a37613
 
6.5%
l34459
 
5.9%
r33674
 
5.8%
30221
 
5.2%
n26104
 
4.5%
o24036
 
4.1%
Other values (44)221625
38.1%

latitude
Real number (ℝ)

High correlation 

Distinct19048
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.728952
Minimum40.49979
Maximum40.91306
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size382.2 KiB
2026-02-09T21:01:27.876801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum40.49979
5-th percentile40.646123
Q140.6901
median40.72308
Q340.76312
95-th percentile40.825637
Maximum40.91306
Range0.41327
Interquartile range (IQR)0.07302

Descriptive statistics

Standard deviation0.054528525
Coefficient of variation (CV)0.0013388148
Kurtosis0.14866877
Mean40.728952
Median Absolute Deviation (MAD)0.03642
Skewness0.23705575
Sum1991890.1
Variance0.00297336
MonotonicityNot monotonic
2026-02-09T21:01:28.021798image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.7181318
 
< 0.1%
40.6941413
 
< 0.1%
40.6844413
 
< 0.1%
40.6863413
 
< 0.1%
40.7618912
 
< 0.1%
40.6853712
 
< 0.1%
40.7117112
 
< 0.1%
40.7135312
 
< 0.1%
40.7612512
 
< 0.1%
40.6905411
 
< 0.1%
Other values (19038)48778
99.7%
ValueCountFrequency (%)
40.499791
< 0.1%
40.506411
< 0.1%
40.507081
< 0.1%
40.508681
< 0.1%
40.508731
< 0.1%
40.509431
< 0.1%
40.511331
< 0.1%
40.522111
< 0.1%
40.522931
< 0.1%
40.5271
< 0.1%
ValueCountFrequency (%)
40.913061
< 0.1%
40.912341
< 0.1%
40.911691
< 0.1%
40.911671
< 0.1%
40.908041
< 0.1%
40.907341
< 0.1%
40.905271
< 0.1%
40.904841
< 0.1%
40.904061
< 0.1%
40.903911
< 0.1%

longitude
Real number (ℝ)

High correlation 

Distinct14718
Distinct (%)30.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-73.952175
Minimum-74.24442
Maximum-73.71299
Zeros0
Zeros (%)0.0%
Negative48906
Negative (%)100.0%
Memory size382.2 KiB
2026-02-09T21:01:28.187849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-74.24442
5-th percentile-74.00388
Q1-73.98308
median-73.955685
Q3-73.936283
95-th percentile-73.865795
Maximum-73.71299
Range0.53143
Interquartile range (IQR)0.0467975

Descriptive statistics

Standard deviation0.046153532
Coefficient of variation (CV)-0.00062409973
Kurtosis5.0227314
Mean-73.952175
Median Absolute Deviation (MAD)0.024845
Skewness1.2844629
Sum-3616705.1
Variance0.0021301485
MonotonicityNot monotonic
2026-02-09T21:01:28.362803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-73.9567718
 
< 0.1%
-73.9542718
 
< 0.1%
-73.9540517
 
< 0.1%
-73.9513616
 
< 0.1%
-73.9533216
 
< 0.1%
-73.950616
 
< 0.1%
-73.9479116
 
< 0.1%
-73.9574215
 
< 0.1%
-73.9453715
 
< 0.1%
-73.9843915
 
< 0.1%
Other values (14708)48744
99.7%
ValueCountFrequency (%)
-74.244421
< 0.1%
-74.242851
< 0.1%
-74.240841
< 0.1%
-74.239861
< 0.1%
-74.239141
< 0.1%
-74.238031
< 0.1%
-74.230591
< 0.1%
-74.212381
< 0.1%
-74.210171
< 0.1%
-74.209411
< 0.1%
ValueCountFrequency (%)
-73.712991
< 0.1%
-73.71691
< 0.1%
-73.717951
< 0.1%
-73.718291
< 0.1%
-73.719281
< 0.1%
-73.721731
< 0.1%
-73.721791
< 0.1%
-73.722471
< 0.1%
-73.724351
< 0.1%
-73.725811
< 0.1%

room_type
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.3 MiB
Entire home/apt
25414 
Private room
22332 
Shared room
 
1160

Length

Max length15
Median length15
Mean length13.535231
Min length11

Characters and Unicode

Total characters661954
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPrivate room
2nd rowEntire home/apt
3rd rowPrivate room
4th rowEntire home/apt
5th rowEntire home/apt

Common Values

ValueCountFrequency (%)
Entire home/apt25414
52.0%
Private room22332
45.7%
Shared room1160
 
2.4%

Length

2026-02-09T21:01:28.502805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-02-09T21:01:28.587789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
entire25414
26.0%
home/apt25414
26.0%
room23492
24.0%
private22332
22.8%
shared1160
 
1.2%

Most occurring characters

ValueCountFrequency (%)
e74320
11.2%
t73160
11.1%
o72398
10.9%
r72398
10.9%
a48906
 
7.4%
48906
 
7.4%
m48906
 
7.4%
i47746
 
7.2%
h26574
 
4.0%
p25414
 
3.8%
Other values (7)123226
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter538728
81.4%
Space Separator48906
 
7.4%
Uppercase Letter48906
 
7.4%
Other Punctuation25414
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e74320
13.8%
t73160
13.6%
o72398
13.4%
r72398
13.4%
a48906
9.1%
m48906
9.1%
i47746
8.9%
h26574
 
4.9%
p25414
 
4.7%
n25414
 
4.7%
Other values (2)23492
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
E25414
52.0%
P22332
45.7%
S1160
 
2.4%
Space Separator
ValueCountFrequency (%)
48906
100.0%
Other Punctuation
ValueCountFrequency (%)
/25414
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin587634
88.8%
Common74320
 
11.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e74320
12.6%
t73160
12.4%
o72398
12.3%
r72398
12.3%
a48906
8.3%
m48906
8.3%
i47746
8.1%
h26574
 
4.5%
p25414
 
4.3%
E25414
 
4.3%
Other values (5)72398
12.3%
Common
ValueCountFrequency (%)
48906
65.8%
/25414
34.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII661954
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e74320
11.2%
t73160
11.1%
o72398
10.9%
r72398
10.9%
a48906
 
7.4%
48906
 
7.4%
m48906
 
7.4%
i47746
 
7.2%
h26574
 
4.0%
p25414
 
3.8%
Other values (7)123226
18.6%

price
Real number (ℝ)

Distinct674
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean152.71132
Minimum0
Maximum10000
Zeros11
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size382.2 KiB
2026-02-09T21:01:28.702797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile40
Q169
median106
Q3175
95-th percentile355
Maximum10000
Range10000
Interquartile range (IQR)106

Descriptive statistics

Standard deviation240.12871
Coefficient of variation (CV)1.5724355
Kurtosis585.79305
Mean152.71132
Median Absolute Deviation (MAD)46
Skewness19.120832
Sum7468500
Variance57661.799
MonotonicityNot monotonic
2026-02-09T21:01:29.092712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1002051
 
4.2%
1502048
 
4.2%
501534
 
3.1%
601459
 
3.0%
2001402
 
2.9%
751370
 
2.8%
801272
 
2.6%
651190
 
2.4%
701170
 
2.4%
1201131
 
2.3%
Other values (664)34279
70.1%
ValueCountFrequency (%)
011
 
< 0.1%
1017
< 0.1%
113
 
< 0.1%
124
 
< 0.1%
131
 
< 0.1%
156
 
< 0.1%
166
 
< 0.1%
182
 
< 0.1%
194
 
< 0.1%
2033
0.1%
ValueCountFrequency (%)
100003
< 0.1%
99993
< 0.1%
85001
 
< 0.1%
80001
 
< 0.1%
77031
 
< 0.1%
75002
< 0.1%
68001
 
< 0.1%
65003
< 0.1%
64191
 
< 0.1%
60002
< 0.1%

minimum_nights
Real number (ℝ)

Skewed 

Distinct109
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0316117
Minimum1
Maximum1250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size382.2 KiB
2026-02-09T21:01:29.246804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q35
95-th percentile30
Maximum1250
Range1249
Interquartile range (IQR)4

Descriptive statistics

Standard deviation20.512489
Coefficient of variation (CV)2.9171817
Kurtosis853.55357
Mean7.0316117
Median Absolute Deviation (MAD)2
Skewness21.817416
Sum343888
Variance420.76219
MonotonicityNot monotonic
2026-02-09T21:01:29.415801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112721
26.0%
211701
23.9%
38000
16.4%
303760
 
7.7%
43304
 
6.8%
53035
 
6.2%
72058
 
4.2%
6752
 
1.5%
14562
 
1.1%
10483
 
1.0%
Other values (99)2530
 
5.2%
ValueCountFrequency (%)
112721
26.0%
211701
23.9%
38000
16.4%
43304
 
6.8%
53035
 
6.2%
6752
 
1.5%
72058
 
4.2%
8130
 
0.3%
980
 
0.2%
10483
 
1.0%
ValueCountFrequency (%)
12501
 
< 0.1%
10001
 
< 0.1%
9993
 
< 0.1%
5005
 
< 0.1%
4801
 
< 0.1%
4001
 
< 0.1%
3701
 
< 0.1%
3661
 
< 0.1%
36529
0.1%
3641
 
< 0.1%

number_of_reviews
Real number (ℝ)

High correlation  Zeros 

Distinct394
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.300454
Minimum0
Maximum629
Zeros10052
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size382.2 KiB
2026-02-09T21:01:29.565794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q324
95-th percentile114
Maximum629
Range629
Interquartile range (IQR)23

Descriptive statistics

Standard deviation44.607175
Coefficient of variation (CV)1.9144337
Kurtosis19.553221
Mean23.300454
Median Absolute Deviation (MAD)5
Skewness3.6926834
Sum1139532
Variance1989.8
MonotonicityNot monotonic
2026-02-09T21:01:29.722810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
010052
20.6%
15244
 
10.7%
23465
 
7.1%
32520
 
5.2%
41994
 
4.1%
51618
 
3.3%
61357
 
2.8%
71179
 
2.4%
81127
 
2.3%
9964
 
2.0%
Other values (384)19386
39.6%
ValueCountFrequency (%)
010052
20.6%
15244
10.7%
23465
 
7.1%
32520
 
5.2%
41994
 
4.1%
51618
 
3.3%
61357
 
2.8%
71179
 
2.4%
81127
 
2.3%
9964
 
2.0%
ValueCountFrequency (%)
6291
< 0.1%
6071
< 0.1%
5971
< 0.1%
5941
< 0.1%
5761
< 0.1%
5431
< 0.1%
5401
< 0.1%
5101
< 0.1%
4881
< 0.1%
4801
< 0.1%

last_review
Date

Missing 

Distinct1764
Distinct (%)4.5%
Missing10052
Missing (%)20.6%
Memory size382.2 KiB
Minimum2011-03-28 00:00:00
Maximum2019-12-06 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-09T21:01:29.876745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:30.034740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

reviews_per_month
Real number (ℝ)

High correlation  Missing 

Distinct937
Distinct (%)2.4%
Missing10052
Missing (%)20.6%
Infinite0
Infinite (%)0.0%
Mean1.3731513
Minimum0.01
Maximum58.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size382.2 KiB
2026-02-09T21:01:30.214394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.04
Q10.19
median0.72
Q32.02
95-th percentile4.64
Maximum58.5
Range58.49
Interquartile range (IQR)1.83

Descriptive statistics

Standard deviation1.6802699
Coefficient of variation (CV)1.2236597
Kurtosis42.499825
Mean1.3731513
Median Absolute Deviation (MAD)0.62
Skewness3.130418
Sum53352.42
Variance2.8233068
MonotonicityNot monotonic
2026-02-09T21:01:30.402492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02919
 
1.9%
1893
 
1.8%
0.05893
 
1.8%
0.03804
 
1.6%
0.16667
 
1.4%
0.04655
 
1.3%
0.08596
 
1.2%
0.09593
 
1.2%
0.06579
 
1.2%
0.11539
 
1.1%
Other values (927)31716
64.9%
(Missing)10052
 
20.6%
ValueCountFrequency (%)
0.0142
 
0.1%
0.02919
1.9%
0.03804
1.6%
0.04655
1.3%
0.05893
1.8%
0.06579
1.2%
0.07466
1.0%
0.08596
1.2%
0.09593
1.2%
0.1457
0.9%
ValueCountFrequency (%)
58.51
< 0.1%
27.951
< 0.1%
20.941
< 0.1%
19.751
< 0.1%
17.821
< 0.1%
16.811
< 0.1%
16.221
< 0.1%
16.031
< 0.1%
15.781
< 0.1%
15.321
< 0.1%
Distinct47
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1427023
Minimum1
Maximum327
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size382.2 KiB
2026-02-09T21:01:30.549490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile15
Maximum327
Range326
Interquartile range (IQR)1

Descriptive statistics

Standard deviation32.948926
Coefficient of variation (CV)4.6129497
Kurtosis67.567017
Mean7.1427023
Median Absolute Deviation (MAD)0
Skewness7.9340992
Sum349321
Variance1085.6318
MonotonicityNot monotonic
2026-02-09T21:01:30.729387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
132312
66.1%
26658
 
13.6%
32854
 
5.8%
41441
 
2.9%
5845
 
1.7%
6570
 
1.2%
8416
 
0.9%
7399
 
0.8%
327327
 
0.7%
9234
 
0.5%
Other values (37)2850
 
5.8%
ValueCountFrequency (%)
132312
66.1%
26658
 
13.6%
32854
 
5.8%
41441
 
2.9%
5845
 
1.7%
6570
 
1.2%
7399
 
0.8%
8416
 
0.9%
9234
 
0.5%
10210
 
0.4%
ValueCountFrequency (%)
327327
0.7%
232232
0.5%
121121
 
0.2%
103103
 
0.2%
96192
0.4%
9191
 
0.2%
8787
 
0.2%
6565
 
0.1%
52104
 
0.2%
5050
 
0.1%

availability_365
Real number (ℝ)

Zeros 

Distinct366
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.78203
Minimum0
Maximum365
Zeros17536
Zeros (%)35.9%
Negative0
Negative (%)0.0%
Memory size382.2 KiB
2026-02-09T21:01:30.913383image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median45
Q3227
95-th percentile359
Maximum365
Range365
Interquartile range (IQR)227

Descriptive statistics

Standard deviation131.62037
Coefficient of variation (CV)1.1670332
Kurtosis-0.99755561
Mean112.78203
Median Absolute Deviation (MAD)45
Skewness0.76338117
Sum5515718
Variance17323.922
MonotonicityNot monotonic
2026-02-09T21:01:31.076496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
017536
35.9%
3651295
 
2.6%
364491
 
1.0%
1408
 
0.8%
89361
 
0.7%
5340
 
0.7%
3306
 
0.6%
179301
 
0.6%
90290
 
0.6%
2270
 
0.6%
Other values (356)27308
55.8%
ValueCountFrequency (%)
017536
35.9%
1408
 
0.8%
2270
 
0.6%
3306
 
0.6%
4233
 
0.5%
5340
 
0.7%
6246
 
0.5%
7219
 
0.4%
8233
 
0.5%
9193
 
0.4%
ValueCountFrequency (%)
3651295
2.6%
364491
 
1.0%
363239
 
0.5%
362166
 
0.3%
361111
 
0.2%
360102
 
0.2%
359135
 
0.3%
358180
 
0.4%
35795
 
0.2%
35678
 
0.2%

Interactions

2026-02-09T21:01:22.372637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:09.924067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:11.656855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:12.974356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:14.220551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:15.485507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:16.760480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:18.027507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:19.527787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:20.885883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:22.505767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:10.072084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:11.816879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:13.090448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:14.350283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:15.611424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:16.887572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:18.164502image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:19.687798image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:21.031661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:22.624864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:10.225173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:11.923979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:13.196496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:14.471513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:15.735399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:17.010245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:18.291518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:19.821808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:21.143645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:22.740754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:10.349449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:12.049984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:13.303353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:14.589516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:15.863427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:17.133149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:18.425505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:19.956800image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:21.257555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:22.860772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:10.547333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-09T21:01:14.713526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:15.999400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:17.257395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:18.579510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:20.094801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:21.432541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:22.981852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:10.755347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:12.312010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:13.520911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:14.831508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:16.116413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:17.378433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:18.712503image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:20.210799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:21.550530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:23.110755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:10.951336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-09T21:01:22.111588image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:23.473881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:11.506855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:12.861347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:14.109713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:15.349403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:16.633569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:17.907394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:19.382783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:20.750794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-09T21:01:22.238646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-09T21:01:31.207399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
availability_365calculated_host_listings_counthost_ididlatitudelongitudeminimum_nightsneighbourhood_groupnumber_of_reviewspricereviews_per_monthroom_type
availability_3651.0000.4070.1730.166-0.0070.0690.0760.0830.2370.0860.3920.087
calculated_host_listings_count0.4071.0000.1470.1350.0030.0640.0640.0890.056-0.1060.1460.097
host_id0.1730.1471.0000.5590.0490.109-0.1300.100-0.129-0.0720.2680.092
id0.1660.1350.5591.0000.0050.071-0.0580.064-0.308-0.0210.3600.070
latitude-0.0070.0030.0490.0051.0000.0350.0220.539-0.0440.136-0.0230.117
longitude0.0690.0640.1090.0710.0351.000-0.1190.6540.080-0.4380.1190.157
minimum_nights0.0760.064-0.130-0.0580.022-0.1191.0000.003-0.1750.101-0.2890.012
neighbourhood_group0.0830.0890.1000.0640.5390.6540.0031.0000.0270.0180.0480.126
number_of_reviews0.2370.056-0.129-0.308-0.0440.080-0.1750.0271.000-0.0550.7060.022
price0.086-0.106-0.072-0.0210.136-0.4380.1010.018-0.0551.000-0.0190.025
reviews_per_month0.3920.1460.2680.360-0.0230.119-0.2890.0480.706-0.0191.0000.029
room_type0.0870.0970.0920.0700.1170.1570.0120.1260.0220.0250.0291.000

Missing values

2026-02-09T21:01:23.713859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-09T21:01:23.934857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2026-02-09T21:01:24.330870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idnamehost_idhost_nameneighbourhood_groupneighbourhoodlatitudelongituderoom_typepriceminimum_nightsnumber_of_reviewslast_reviewreviews_per_monthcalculated_host_listings_countavailability_365
02539Clean & quiet apt home by the park2787JohnBrooklynKensington40.64749-73.97237Private room1491919-10-20180.216365
12595Skylit Midtown Castle2845JenniferManhattanMidtown40.75362-73.98377Entire home/apt22514521-05-20190.382355
23647THE VILLAGE OF HARLEM....NEW YORK !4632ElisabethManhattanHarlem40.80902-73.94190Private room15030NaNNaN1365
33831Cozy Entire Floor of Brownstone4869LisaRoxanneBrooklynClinton Hill40.68514-73.95976Entire home/apt89127005-07-20194.641194
45022Entire Apt: Spacious Studio/Loft by central park7192LauraManhattanEast Harlem40.79851-73.94399Entire home/apt8010919-11-20180.1010
55099Large Cozy 1 BR Apartment In Midtown East7322ChrisManhattanMurray Hill40.74767-73.97500Entire home/apt20037422-06-20190.591129
65121BlissArtsSpace!7356GaronBrooklynBedford-Stuyvesant40.68688-73.95596Private room60454905-10-20170.4010
75178Large Furnished Room Near B'way8967ShunichiManhattanHell's Kitchen40.76489-73.98493Private room79243024-06-20193.471220
85203Cozy Clean Guest Room - Family Apt7490MaryEllenManhattanUpper West Side40.80178-73.96723Private room79211821-07-20170.9910
95238Cute & Cozy Lower East Side 1 bdrm7549BenManhattanChinatown40.71344-73.99037Entire home/apt150116009-06-20191.334188
idnamehost_idhost_nameneighbourhood_groupneighbourhoodlatitudelongituderoom_typepriceminimum_nightsnumber_of_reviewslast_reviewreviews_per_monthcalculated_host_listings_countavailability_365
488965121BlissArtsSpace!7356GaronBrooklynBedford-Stuyvesant40.68688-73.95596Private room60454905-10-20170.4010
488975178Large Furnished Room Near B'way8967ShunichiManhattanHell's Kitchen40.76489-73.98493Private room79243024-06-20193.471220
488985203Cozy Clean Guest Room - Family Apt7490MaryEllenManhattanUpper West Side40.80178-73.96723Private room79211821-07-20170.9910
488995238Cute & Cozy Lower East Side 1 bdrm7549BenManhattanChinatown40.71344-73.99037Entire home/apt150116009-06-20191.334188
489005295Beautiful 1br on Upper West Side7702LenaManhattanUpper West Side40.80316-73.96545Entire home/apt13555322-06-20190.4316
489015441Central Manhattan/near Broadway7989KateManhattanHell's Kitchen40.76076-73.98867Private room85218823-06-20191.50139
489025803Lovely Room 1, Garden, Best Area, Legal rental9744LaurieBrooklynSouth Slope40.66829-73.98779Private room89416724-06-20191.343314
489036021Wonderful Guest Bedroom in Manhattan for SINGLES11528ClaudioManhattanUpper West Side40.79826-73.96113Private room85211305-07-20190.911333
489046090West Village Nest - Superhost11975AlinaManhattanWest Village40.73530-74.00525Entire home/apt120902731-10-20180.2210
489056848Only 2 stops to Manhattan studio15991Allen & IrinaBrooklynWilliamsburg40.70837-73.95352Entire home/apt140214829-06-20191.20146

Duplicate rows

Most frequently occurring

idnamehost_idhost_nameneighbourhood_groupneighbourhoodlatitudelongituderoom_typepriceminimum_nightsnumber_of_reviewslast_reviewreviews_per_monthcalculated_host_listings_countavailability_365# duplicates
05099Large Cozy 1 BR Apartment In Midtown East7322ChrisManhattanMurray Hill40.74767-73.97500Entire home/apt20037422-06-20190.5911292
15121BlissArtsSpace!7356GaronBrooklynBedford-Stuyvesant40.68688-73.95596Private room60454905-10-20170.40102
25178Large Furnished Room Near B'way8967ShunichiManhattanHell's Kitchen40.76489-73.98493Private room79243024-06-20193.4712202
35203Cozy Clean Guest Room - Family Apt7490MaryEllenManhattanUpper West Side40.80178-73.96723Private room79211821-07-20170.99102
45238Cute & Cozy Lower East Side 1 bdrm7549BenManhattanChinatown40.71344-73.99037Entire home/apt150116009-06-20191.3341882
55295Beautiful 1br on Upper West Side7702LenaManhattanUpper West Side40.80316-73.96545Entire home/apt13555322-06-20190.43162
65441Central Manhattan/near Broadway7989KateManhattanHell's Kitchen40.76076-73.98867Private room85218823-06-20191.501392
75803Lovely Room 1, Garden, Best Area, Legal rental9744LaurieBrooklynSouth Slope40.66829-73.98779Private room89416724-06-20191.3433142
86021Wonderful Guest Bedroom in Manhattan for SINGLES11528ClaudioManhattanUpper West Side40.79826-73.96113Private room85211305-07-20190.9113332
96090West Village Nest - Superhost11975AlinaManhattanWest Village40.73530-74.00525Entire home/apt120902731-10-20180.22102